 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8BUR4 from www.uniprot.org...
The NucPred score for your sequence is 0.74 (see score help below)
1 MTRWVPTKREEKYGVAFYNYDARGADELSLQIGDTVHILETYEGWYRGYT 50
51 LRKKSKKGIFPASYIHLKEAIVEGKGQHETVIPGDLPLIQEVTTTLREWS 100
101 TIWRQLYVQDNREMFRSVRHMIYDLIEWRSQILSGTLPQDELKELKKKVT 150
151 AKIDYGNRILDLDLVVRDEDGNILDPELTSTISLFRAHEVASKQVEERLQ 200
201 EEKSQKQNMDINRQAKFAATPSLALFVNLKNVVCKIGEDAEVLMSLYDPM 250
251 ESKFISENYLVRWSSSGLPKDIDRLHNLRAVFTDLGSKDLKREKISFVCQ 300
301 IVRVGRMELRDSNTRKLTSGLRRPFGVAVMDVTDIINGKVDDEDKQHFIP 350
351 FQAVAGENDFLQTVINKVIAAKEVNHKGQGLWVTLKLLPGDIHQIRKEFP 400
401 HLVDRTTAVARKTGFPEIIMPGDVRNDIYVTLVQGDFDKGSKTTAKNVEV 450
451 TVSVYDEDGKRLEHVIFPGAGDEAISEYKSVIYYQVKQPRWFETLKVAIP 500
501 IEDVNRSHLRFTFRHRSSQDSKDKSEKIFALAFVKLMRYDGTTLRDGEHD 550
551 LIVYKAEAKKLEDAATYLSLPSTKGELEEKGHSATGKGMQSLGSCTISKD 600
601 SFQISTLVCSTKLTQNVDLLGLLKWRSNTNLLQQNLRQLMKVDGGEVVKF 650
651 LQDTLDALFNIMMENSESETFDTLVFDALVFIIGLIADRKFQHFNPVLET 700
701 YIKKHFSATLAYTKLTKVLRTYVASAEKPGVNEQLYKAIKALEYIFKFIV 750
751 RSRVLFNQLYENKGEADFVESLLQLFRSINDMMSSLSELTVRVKGAALKY 800
801 LPTIVNDVKLVFDPKELSKMFTEFILNVPAGLLTVQKLSCLIEIVHSDLF 850
851 TQHDCREILLPMMTDQLKYHLERQEELEACCQLLSNILEVLYRKDVGPTQ 900
901 RHVQIIMETLLRTVNRTVISMGRDSELIGNFVACMTAILRQMEDYHYAHL 950
951 IKTFGKMRTDVVDFLMETFIMFKNLIGKNVYPFDWVIMNTMQNKVFLRAI 1000
1001 NQYADMLNKRFLDQANFELQLWNNYFHLAVAFLTQESLQLENFSSAKRAK 1050
1051 ILNKYGDMRRQIGFEIRDMWYNLGQHKIKFIPEMVGPILEMTLIPETELR 1100
1101 KATLPIFFDMMQCEFHSTRSFQMFENEIITKLDHEVEGGRGDEQYKVLFD 1150
1151 KILLEHCRKHKYLAKTGETFVKLVVRLMERLLDYRTIMHDENKDNRMSCT 1200
1201 VNVLNFYKEIEREEMYIRYLYKLCDLHKECDNYTEAAYTLLLHAKLLKWS 1250
1251 EDVCAAHLTQRDGFQATTQGQLKEQLYQEIIHYFDKGKMWEEAIALGKEL 1300
1301 AEQYETEMFDYEQLSELLKKQAQFYENIVKVIRPKPDYFAVGYYGQGFPS 1350
1351 FLRGKVFIYRGKEYERREDFEARLLTQFPNAEKMKTTSPPGDDIKTSPGQ 1400
1401 YIQCFTVKPKLDLPPRFHRPVSEQIVSFYRVNEVQRFEYSRPIRKGEKNP 1450
1451 DNEFANMWIERTIYTTAYKLPGILRWFEVKSVFMVEISPLENAIETMQLT 1500
1501 NDKISSMVQQHLDDPGLPINPLSMLLNGIVDPAVMGGFANYEKAFFTDRY 1550
1551 LQEHPEAHGQIEKLKDLIAWQIPFLAEGIRIHGDKVTEALRPFHERMEAC 1600
1601 FKQLKEKVEKQYGVRTMPSGLDDRRGSRPRSMVRSFTMPSSSRPLSVASV 1650
1651 SSFSSDSTPSRPGSDGFALEPLLPKKMHSRSQDKLDKDDPDKEKKDKKKE 1700
1701 KRNSKHQEIFDKEFKPADSSLQQSEAVILSETISPLRPQRPKSQVINVIG 1750
1751 NERRFSVSPASPSSQQTPPPVTPRAKLSFSIQPSLELNGMMGMDVADVPP 1800
1801 PLPLKGNMADYGNLMENQDMMVSPTSPPPPPPQRQQPPPLPSKTPPPPPP 1850
1851 KTTRKQTSVDSGIVQ 1865
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
What does the NucPred score mean?
| You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper. |
| NucPred score threshold | Specificity | Sensitivity |
| see above | fraction of proteins predicted to be nuclear that actually are nuclear | fraction of true nuclear proteins that are predicted (coverage) |
| 0.10 | 0.45 | 0.88 |
| 0.20 | 0.52 | 0.83 |
| 0.30 | 0.57 | 0.77 |
| 0.40 | 0.63 | 0.69 |
| 0.50 | 0.70 | 0.62 |
| 0.60 | 0.71 | 0.53 |
| 0.70 | 0.81 | 0.44 |
| 0.80 | 0.84 | 0.32 |
| 0.90 | 0.88 | 0.21 |
| 1.00 | 1.00 | 0.02 |
| Sequences which score >= 0.8 with NucPred and which
are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.) |
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